Header logo is ei

Towards Motor Skill Learning for Robotics


Conference Paper


Learning robots that can acquire new motor skills and refine existing one has been a long standing vision of robotics, artificial intelligence, and the cognitive sciences. Early steps towards this goal in the 1980s made clear that reasoning and human insights will not suffice. Instead, new hope has been offered by the rise of modern machine learning approaches. However, to date, it becomes increasingly clear that off-the-shelf machine learning approaches will not suffice for motor skill learning as these methods often do not scale into the high-dimensional domains of manipulator and humanoid robotics nor do they fulfill the real-time requirement of our domain. As an alternative, we propose to break the generic skill learning problem into parts that we can understand well from a robotics point of view. After designing appropriate learning approaches for these basic components, these will serve as the ingredients of a general approach to motor skill learning. In this paper, we discuss our recent and current progress in this direction. For doing so, we present our work on learning to control, on learning elementary movements as well as our steps towards learning of complex tasks. We show several evaluations both using real robots as well as physically realistic simulations.

Author(s): Peters, J. and Mülling, K. and Kober, J. and Nguyen-Tuong, D. and Kroemer, O.
Book Title: Robotics Research
Journal: Proceedings of the 14th International Symposium on Robotics Research (ISRR 2009)
Pages: 469-482
Year: 2011
Month: January
Day: 0
Editors: Pradalier, C. , R. Siegwart, G. Hirzinger
Publisher: Springer

Department(s): Empirical Inference
Bibtex Type: Conference Paper (inproceedings)

DOI: 10.1007/978-3-642-19457-3_28
Event Name: 14th International Symposium on Robotics Research (ISRR 2009)
Event Place: Luzern, Switzerland

Address: Berlin, Germany
Digital: 0
ISBN: 978-3-642-19456-6
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

Links: PDF


  title = {Towards Motor Skill Learning for Robotics},
  author = {Peters, J. and M{\"u}lling, K. and Kober, J. and Nguyen-Tuong, D. and Kroemer, O.},
  journal = {Proceedings of the 14th International Symposium on Robotics Research (ISRR 2009)},
  booktitle = {Robotics Research},
  pages = {469-482},
  editors = {Pradalier, C. , R. Siegwart, G. Hirzinger},
  publisher = {Springer},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {Berlin, Germany},
  month = jan,
  year = {2011},
  month_numeric = {1}